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Proceedings Paper

Real-time 2D/3D registration for tumor motion tracking during radiotherapy
Author(s): H. Furtado; C. Gendrin; C. Bloch; J. Spoerk; S. A. Pawiro; C. Weber; M. Figl; M. Stock; D. Georg; H. Bergmann; W. Birkfellner
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Paper Abstract

Organ motion during radiotherapy is one of causes of uncertainty in dose delivery. To cope with this, the planned target volume (PTV) has to be larger than needed to guarantee full tumor irradiation. Existing methods deal with the problem by performing tumor tracking using implanted fiducial markers or magnetic sensors. In this work, we investigate the feasibility of using x-ray based real time 2D/3D registration for non-invasive tumor motion tracking during radiotherapy. Our method uses purely intensity based techniques, thus avoiding markers or fiducials. X-rays are acquired during treatment at a rate of 5.4Hz. We iteratively compare each x-ray with a set of digitally reconstructed radiographs (DRR) generated from the planning volume dataset, finding the optimal match between the x-ray and one of the DRRs. The DRRs are generated using a ray-casting algorithm, implemented using general purpose computation on graphics hardware (GPGPU) programming techniques using CUDA for greater performance. Validation is conducted off-line using a phantom and five clinical patient data sets. The registration is performed on a region of interest (ROI) centered around the PTV. The phantom motion is measured with an rms error of 2.1 mm and mean registration time is 220 ms. For the patient data sets, a sinusoidal movement that clearly correlates to the breathing cycle is seen. Mean registration time is always under 105 ms which is well suited for our purposes. These results demonstrate that real-time organ motion monitoring using image based markerless registration is feasible.

Paper Details

Date Published: 14 February 2012
PDF: 8 pages
Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 831407 (14 February 2012); doi: 10.1117/12.910117
Show Author Affiliations
H. Furtado, Medical Univ. Vienna (Austria)
C. Gendrin, Medical Univ. Vienna (Austria)
C. Bloch, Medical Univ. Vienna (Austria)
J. Spoerk, Medical Univ. Vienna (Austria)
S. A. Pawiro, Medical Univ. Vienna (Austria)
C. Weber, Medical Univ. Vienna (Austria)
M. Figl, Medical Univ. Vienna (Austria)
M. Stock, Medical Univ. Vienna (Austria)
D. Georg, Medical Univ. Vienna (Austria)
H. Bergmann, Medical Univ. Vienna (Austria)
W. Birkfellner, Medical Univ. Vienna (Austria)

Published in SPIE Proceedings Vol. 8314:
Medical Imaging 2012: Image Processing
David R. Haynor; Sébastien Ourselin, Editor(s)

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